Pongpech Nisha, Avihingsanon Anchalee, Chaiwarith Romanee, Kantipong Pacharee, Boettiger David, Ross Jeremy, Kiertiburanakul Sasisopin
Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
HIV-NAT/Thai Red Cross AIDS Research Centre, Bangkok, Thailand.
Southeast Asian J Trop Med Public Health. 2018 Nov;49(6):965-974.
A prediction model for pretreatment HIV RNA level ≤100,000 copies/ml would provide a useful tool for selection of abacavir (ABC) or rilpivirine (RPV) in the first-line regimen in a resource-limited setting. Factors associated with pre-treatment HIV RNA ≤100,000 copies/ml were determined from a cohort of 1,223 patients divided into a derivation (n = 873) and the remaining in a validation group. Their median [interquartile range (IQR)] age was 36.3 (30.5-42.9) years, CD4 count 122 (39-216) cells/mm3 and pre-treatment HIV RNA level 100,000 (32,449-229,777) copies/ml. Factors associated with pretreatment HIV RNA ≤100,000 copies/ml were non-anemia [odds ratio (OR)= 2.05; 95% confidence interval (CI): 1.28-3.27, p= 0.003], CD4 count ≥200 cells/mm3 (OR= 3.00; 95% CI: 2.08-4.33, p<0.001) and non-heterosexual HIV exposure (OR= 1.61; 95% CI: 1.07-2.43, p= 0.021). The area under a receiver operating characteristic curve was 0.66 (95% CI: 0.62-0.69), but specificity was 97.3%. The prediction model identified a set of readily available clinical data but lacked the requisite predictive performance to fulfill its purpose.
一种用于预测治疗前HIV RNA水平≤100,000拷贝/毫升的模型，可为在资源有限的环境中一线治疗方案中选择阿巴卡韦（ABC）或利匹韦林（RPV）提供有用工具。从1223名患者队列中确定与治疗前HIV RNA≤100,000拷贝/毫升相关的因素，该队列分为推导组（n = 873），其余为验证组。他们的年龄中位数[四分位间距（IQR）]为36.3（30.5 - 42.9）岁，CD4细胞计数为122（39 - 216）个/立方毫米，治疗前HIV RNA水平为100,000（32,449 - 229,777）拷贝/毫升。与治疗前HIV RNA≤100,000拷贝/毫升相关的因素为非贫血[比值比（OR）= 2.05；95%置信区间（CI）：1.28 - 3.27，p = 0.003]、CD4细胞计数≥200个/立方毫米（OR = 3.00；95% CI：2.08 - 4.33，p < 0.001）和非异性传播HIV感染（OR = 1.61；95% CI：1.07 - 2.43，p = 0.021）。受试者工作特征曲线下面积为0.66（95% CI：0.62 - 0.69），但特异性为97.3%。该预测模型确定了一组易于获得的临床数据，但缺乏实现其目的所需的预测性能。
